Abstract:
The increasing use of Generative AI tools like ChatGPT in higher education
has raised concerns about academic integrity and the efficacy of traditional
assessment methods (AlAli & Wardat, 2024). This study, which was
conducted in a leading non-state higher educational institute of Sri Lanka,
explores how the faculty members in an undergraduate literature program
perceive and adapt their assessment practices in response to the growing
presence of AI tools. Semi-structured interviews with six lecturers teaching
literature provided qualitative insights into their views on AI’s impact on
student assessments, while document analysis of assignment guidelines,
marking rubrics, and assessment policies helped to contextualize institutional
responses to these challenges. The findings revealed a predominantly negative
perception of lecturers towards ChatGPT, with faculty viewing it as a threat
to the authenticity and originality of student submissions. However, revealed
through document analysis it also highlights a gap in how faculty are adapting
their assessment strategies to counter AI’s influence on student submissions.
Many lecturers continue to rely on traditional essay-based assignments
focused on evaluating students’ creative writing and analytical skills, without
focusing on the process of writing or considering the potential use of AI tools.
In response to concerns over AI-driven academic dishonesty, the faculty have
shifted to in-class tests as a perceived solution. The study suggests that faculty
reconsider their existing assessment practices and engage in developing more
adaptive strategies. Faculty could collaborate to design an assessment toolkit
for literature subjects, incorporating assignment templates, process-based
assessment rubrics, and other resources to challenge AI-generated content
while ensuring academic integrity.
